Python is a general purpose programming language that has been embraced by the earth science community for analysis, visualization and data exploration. Geoscience professionals are replacing collections of poorly integrated software tools and languages with this general purpose programming language that can handle remote data requests, statistics, analysis, and visualization. As a result, the Unidata 2018 Proposal highlights the Python programming language and ecosystem as an area where Unidata should focus efforts to benefit the core community. To that end, we have initiated Python training and software projects centered around existing Unidata technology.

MetPy

MetPy is a collection of tools in Python for reading, visualizing, and performing calculations with weather data. MetPy is still in an early stage of development, but you can read more here.

Siphon

Siphon is a collection of Python utilities for downloading data from remote data services. Much of Siphon’s current functionality focuses on access to data hosted on a THREDDS Data Server, although access to data hosted by other web technologies is being quickly added. Siphon is still in an early stage of development, but you can read more here.

Unidata Python Workshop

Unidata Program Center staff have been conducting python training workshops as part of Unidata's annual software training workshops since 2013. Python notebooks used in the workshop are available on Github.

Online Python Training

With support from the National Science Foundation, Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic set of freely available tools that are generally useful to scientists, educators, and students in the geosciences, broadly defined.

Visit Unidata's Online Python Training

Python Gallery

Unidata staff have put together a selection of interesting Jupyter notebooks featuring techniques used in MetPy and elsewhere. Check it out.

netcdf4-python

Unidata Program Center staff assist author Jeff Whitaker in maintaining the netcdf4-python module, which is a Python interface to the netCDF C library. The module can read and write files in both the netCDF 4 and netCDF 3 formats, and can create files that are readable by HDF5 clients. The API modelled after Scientific.IO.NetCDF, and should be familiar to users of that module. More information about netcdf4-python is available on Github.

AWIPS II Python Data Access Framework

The AWIPS II Python Data Access Framework (DAF) provides access to an AWIPS II Environmental Data EXchange (EDEX) server directly from Python code. The DAF strengthens Unidata's AWIPS II offerings by making it easier to retrieve data from the AWIPS II data storage system from outside the Common AWIPS Visualization Environment (CAVE).